The journal of pain : official journal of the American Pain Society
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High interindividual variability in postoperative opioid consumption is related to genetic and environmental factors. We tested the association between morphine consumption, postoperative pain, and single nucleotide polymorphisms (SNPs) within opioid receptor μ 1 (OPRM1), catechol-O-methyltransferase (COMT), uridine diphosphate glucose-glucuronosyltransferase-2B7, and estrogen receptor (ESR1) gene loci to elucidate genetic prediction of opioid consumption. We analyzed 20 SNPs in 201 unrelated Caucasian patients who underwent abdominal surgery and who were receiving postoperative patient-controlled analgesia-administered morphine. Morphine consumption and pain intensity were dependent variables; age and sex were covariates. A haplotype of 7 SNPs in OPRM1 showed significant additive effects on opioid consumption (P = .007); a linear regression model including age and 9 SNPs in ESR1, OPRM1, and COMT explained the highest proportion of variance of morphine consumption (10.7%; P = .001). The minimal model including 3 SNPs in ESR1, OPRM1, and COMT explained 5% of variance (P = .007). We found a significant interaction between rs4680 in COMT and rs4986936 in ESR1 (P = .007) on opioid consumption. SNPs rs677830 and rs540825 of OPRM1 and rs9340799 of ESR1 were nominally associated with pain Numeric Rating Scale scores. Combinations of genetic variants within OPRM1, COMT, and ESR1 better explain variability in morphine consumption than single genetic variants. Our results contribute to the development of genetic markers and statistical models for future diagnostic tools for opioid consumption/efficacy. ⋯ This article presents the efforts dedicated to detect correlations between the genetic polymorphisms and the clinical morphine effect self-administered by patients using a patient-controlled analgesia pump after major surgery. The clinical effect is expressed in terms of morphine consumption and pain scores. REGISTERED ON CLINICALTRIALS.GOV: NCT01233752.
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Evidence from a number of sources supports the existence of two relatively independent neurophysiological systems that underlie avoidance- and approach-related emotions, cognitions, and behavior. There is considerable overlap between 1) the emotions, cognitions, and behaviors controlled by these two systems, and 2) the known effects of chronic pain. Here we propose a 2-factor model of chronic pain on the basis of these well established 2-factor models, and discuss the implications of the model for understanding the effects of pain and mechanisms of psychological pain treatments. The model makes specific hypotheses, which are unique to the proposed model, regarding the mechanisms underlying pain's negative influence and the benefits of psychological pain treatments. The model also provides an overarching framework that could enhance outcomes by 1) broadening the assessment of factors that may be influencing pain and its effect on individual patients, and 2) suggesting that specific techniques from different treatments may be combined to better target these factors. ⋯ The 2-factor model presented in this report provides a framework for understanding the effects of psychological pain treatments, and makes specific a priori hypotheses regarding the specific mechanisms of those treatments. Clinical applications of the model have the potential for enhancing treatment outcomes.